Senior Staff Bioinformatics Scientist (AI-guided protein engineering)

About the role

Illumina is seeking a Senior Staff Scientist to build computational tools and a data foundation for its protein engineering group across global enzyme engineering programs. The role connects data structures for high-throughput and mid-throughput screening, takes part in method development and evaluation, and helps establish semi-closed-loop and closed-loop design-build-test-learn workflows. It provides senior technical leadership at the interface of protein engineering, AI/ML design, screening data systems, automation and experimental execution, and defines how screening results become reusable data assets and how computational methods are benchmarked and adopted. The position is based in Singapore.

Key responsibilities

• Build reusable data foundations for protein engineering, defining data structures, metadata standards, variant lineage, assay context, controls, replicate handling, uncertainty and negative data capture across screening workflows.
• Enable model-guided enzyme engineering by developing and evaluating computational workflows linking sequence, structure, assay and screening datasets to AI/ML models, design rationale, variant prioritization and next-round library design.
• Benchmark computational and AI methods against internal pipelines, open-source methods, commercial protein design platforms and emerging scientific agents.
• Deliver practical tools such as scripts, templates, dashboards, lightweight applications and analysis pipelines for project teams.
• Advance closed-loop DBTL workflows so experimental results are captured, analyzed, modeled, reviewed and turned into design recommendations.
• Partner with experimental scientists, automation, informatics, software and data engineering, chemists, biophysicists and platform teams.

Required profile

• Ph.D. in computational chemistry, computational biology, bioinformatics, computer science or a related field, or equivalent experience.
• Significant experience leading computational biology, protein engineering, AI/ML, screening analytics or scientific data infrastructure efforts.
• Deep experience applying computational or data-driven methods to protein engineering, enzyme engineering, directed evolution or assay analysis.
• Demonstrated ability to design data structures or analytical systems supporting reproducible analysis and cross-project learning.
• Wet-lab experience in high-throughput or mid-throughput screening and/or biochemical assays.
• Excellent communication skills and ability to integrate quickly into cross-functional teams.

Required skills

• Solid programming in at least one major language (C++, Python, R).
• In-depth knowledge of protein sequence or structure modelling, protein-ligand interaction prediction and/or molecular simulations.
• Understanding of AI/ML methods and practical experience with AI/ML-driven protein-design models.
• Strong fundamentals in statistical modelling, algorithm design, data analysis and visualization.
• Preferred: deep learning frameworks (PyTorch, TensorFlow, JAX), molecular modelling software (Rosetta), bioinformatics databases, UNIX and shell scripting, HPC and GPU computing, and knowledge of next-generation sequencing.